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Publications of 2012
Result of the query in the list of publications :
2 Articles |
1 - Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics.
C. Benedek and X. Descombes and J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 34(1): pages 33-50, January 2012.
Keywords : Building extraction, Change detection, Marked point process, multiple birth-and-death dynamics.
Copyright : IEEE
@ARTICLE{benedekPAMI11,
|
| author |
= |
{Benedek, C. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics}, |
| year |
= |
{2012}, |
| month |
= |
{January}, |
| journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
| volume |
= |
{34}, |
| number |
= |
{1}, |
| pages |
= |
{33-50}, |
| url |
= |
{http://dx.doi.org/10.1109/TPAMI.2011.94}, |
| keyword |
= |
{Building extraction, Change detection, Marked point process, multiple birth-and-death dynamics} |
| } |
Abstract :
In this paper we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: (1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low level change information between the time layers and object level building description to recognize and separate changed and unaltered buildings. (2) To answering the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature based modules. (3) To simultaneously ensure the convergence, optimality and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel non-uniform stochastic object birth process, which generates relevant objects with higher probability based on low-level image features. |
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2 - Classification of Very High Resolution SAR Images of Urban Areas Using Copulas and Texture in a Hierarchical Markov Random Field Model.
A. Voisin and V. Krylov and G. Moser and S.B. Serpico and J. Zerubia. IEEE Geoscience and Remote Sensing Letters, 2012.
Note : to appear in 2013
Keywords : Hierarchical Markov random fields (MRFs) , Supervised classification, synthetic aperture radar (SAR), Textural features, urban areas, wavelets.
@ARTICLE{Voisin13,
|
| author |
= |
{Voisin, A. and Krylov, V. and Moser, G. and Serpico, S.B. and Zerubia, J.}, |
| title |
= |
{Classification of Very High Resolution SAR Images of Urban Areas Using Copulas and Texture in a Hierarchical Markov Random Field Model}, |
| year |
= |
{2012}, |
| journal |
= |
{IEEE Geoscience and Remote Sensing Letters}, |
| note |
= |
{to appear in 2013}, |
| url |
= |
{http://dx.doi.org/10.1109/LGRS.2012.2193869}, |
| keyword |
= |
{Hierarchical Markov random fields (MRFs) , Supervised classification, synthetic aperture radar (SAR), Textural features, urban areas, wavelets} |
| } |
|
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5 Conference articles |
1 - Change detection with synthetic aperture radar images by Wilcoxon statistic likelihood ratio test.
V. Krylov and G. Moser and A. Voisin and S.B. Serpico and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Orlando, United States, October 2012.
@INPROCEEDINGS{ICIP12,
|
| author |
= |
{Krylov, V. and Moser, G. and Voisin, A. and Serpico, S.B. and Zerubia, J.}, |
| title |
= |
{Change detection with synthetic aperture radar images by Wilcoxon statistic likelihood ratio test}, |
| year |
= |
{2012}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Orlando, United States}, |
| url |
= |
{http://hal.inria.fr/hal-00724284}, |
| keyword |
= |
{} |
| } |
|
2 - Classification of multi-sensor remote sensing images using an adaptive hierarchical Markovian model.
A. Voisin and V. Krylov and G. Moser and S.B. Serpico and J. Zerubia. In EURASIP, Bucarest, Romania, August 2012.
@INPROCEEDINGS{EURASIP12,
|
| author |
= |
{Voisin, A. and Krylov, V. and Moser, G. and Serpico, S.B. and Zerubia, J.}, |
| title |
= |
{Classification of multi-sensor remote sensing images using an adaptive hierarchical Markovian model}, |
| year |
= |
{2012}, |
| month |
= |
{August}, |
| booktitle |
= |
{EURASIP}, |
| address |
= |
{Bucarest, Romania}, |
| url |
= |
{http://hal.inria.fr/hal-00723286}, |
| keyword |
= |
{} |
| } |
|
3 - A Comparison of Texture and Amplitude based Unsupervised SAR Image Classifications for Urban Area Extraction.
K. Kayabol and J. Zerubia. In IEEE International Geoscience and Remote Sensing Symposium, pages 4054-4057, Munich, Germany, July 2012.
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4 - An hierarchical approach for model-based classification of SAR images.
K. Kayabol and J. Zerubia. In 20th Signal Processing and Communications Applications Conference, Mugla, Turkey, April 2012.
@INPROCEEDINGS{Kayabol12,
|
| author |
= |
{Kayabol, K. and Zerubia, J.}, |
| title |
= |
{An hierarchical approach for model-based classification of SAR images}, |
| year |
= |
{2012}, |
| month |
= |
{April}, |
| booktitle |
= |
{20th Signal Processing and Communications Applications Conference}, |
| address |
= |
{Mugla, Turkey}, |
| url |
= |
{http://hal.inria.fr/hal-00686658}, |
| keyword |
= |
{} |
| } |
|
5 - Multichannel hierarchical image classification using multivariate copulas.
A. Voisin and V. Krylov and G. Moser and S.B. Serpico and J. Zerubia. In IS&T/SPIE Electronic Imaging – Computational Imaging X, San Francisco, United States, January 2012.
@INPROCEEDINGS{SPIE12,
|
| author |
= |
{Voisin, A. and Krylov, V. and Moser, G. and Serpico, S.B. and Zerubia, J.}, |
| title |
= |
{Multichannel hierarchical image classification using multivariate copulas}, |
| year |
= |
{2012}, |
| month |
= |
{January}, |
| booktitle |
= |
{IS&T/SPIE Electronic Imaging – Computational Imaging X}, |
| address |
= |
{San Francisco, United States}, |
| url |
= |
{http://dx.doi.org/10.1117/12.917298}, |
| keyword |
= |
{} |
| } |
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Collection article or Book chapter |
1 - Probability Density Function Estimation for Classification of High Resolution SAR Images.
V. Krylov and G. Moser and S. Serduc and J. Zerubia. In Signal Processing for Remote Sensing, Second Edition, pages 339-363, Ed. C. Chen., Publ. Taylor & Francis, February 2012.
@INCOLLECTION{Taylor12,
|
| author |
= |
{Krylov, V. and Moser, G. and Serduc, S. and Zerubia, J.}, |
| title |
= |
{Probability Density Function Estimation for Classification of High Resolution SAR Images}, |
| year |
= |
{2012}, |
| month |
= |
{February}, |
| booktitle |
= |
{Signal Processing for Remote Sensing, Second Edition}, |
| pages |
= |
{339-363}, |
| editor |
= |
{C. Chen.}, |
| publisher |
= |
{Taylor & Francis}, |
| url |
= |
{https://www.crcpress.com/Signal-and-Image-Processing-for-Remote-Sensing-Second-Edition/Chen/9781439855966}, |
| pdf |
= |
{https://hal.inria.fr/hal-00729044/document}, |
| keyword |
= |
{} |
| } |
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Book |
1 - Markov Random Fields in Image Segmentation. Collection Foundation and Trends in Signal Processing.
Z. Kato and J. Zerubia. Publ. Now Editor, World Scientific, September 2012.
@BOOK{NowPublishers12,
|
| author |
= |
{Kato, Z. and Zerubia, J.}, |
| title |
= |
{Markov Random Fields in Image Segmentation. Collection Foundation and Trends in Signal Processing}, |
| year |
= |
{2012}, |
| month |
= |
{September}, |
| publisher |
= |
{Now Editor, World Scientific}, |
| url |
= |
{http://www.nowpublishers.com/articles/foundations-and-trends-in-signal-processing/SIG-035}, |
| keyword |
= |
{} |
| } |
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